Quantitative Developer — Research Systems — Albuquerque

This fully remote Quantitative Developer — Research Systems opening serves Albuquerque, NM and will build the research platform used to create reproducible market studies at scale. Applicants must be based in the Albuquerque, NM area. The position adds Mountain Time monitoring across both early-market and late-session operating windows.

Compensation and Benefits

About the Role

The Albuquerque, NM position owns research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads. Its working schedule covers Mountain Time monitoring across both early-market and late-session operating windows. You will work with a small group of specialists and preserve enough evidence for another person to challenge every material decision.

Albuquerque Operating Focus

The Albuquerque opening emphasizes cross-time-zone continuity, unambiguous ownership, and measured incident response. Mountain Time coverage spans early national-market work and the later review window. The opening maintains continuity when responsibility moves between regions, with special attention to data timestamps and unfinished decisions. Incident response favors measured containment first, followed by analysis that can distinguish cause from correlation. For this role, that means direct ownership of research-platform reliability, experiment lineage, and large time-series workloads during Mountain Time monitoring across both early-market and late-session operating windows.

First Review Cycle

The initial Albuquerque, NM review combines Mountain Time monitoring across both early-market and late-session operating windows with a controlled examination of research-platform reliability, experiment lineage, and large time-series workloads. Each material observation needs a source, a time, and a defined owner. The evidence package includes this task: Develop reusable data and backtest infrastructure. It also includes this task: Improve experiment tracking, lineage, and reproducibility. The Albuquerque opening emphasizes cross-time-zone continuity, unambiguous ownership, and measured incident response. A peer will review both results from the same source data. Completion requires a repeatable evidence path, a clear response boundary, and a time for the next check. Those records must connect directly to research infrastructure, point-in-time data integrity, experiment lineage, and reliable numerical workloads.

Responsibilities

• Develop reusable data and backtest infrastructure
• Improve experiment tracking, lineage, and reproducibility
• Optimize large time-series workloads
• Add tests that detect leakage and inconsistent data vintages
• Own research-platform reliability, experiment lineage, and large time-series workloads during Mountain Time monitoring across both early-market and late-session operating windows.

Required Qualifications

• Production Python and SQL experience
• Strong knowledge of distributed data systems and numerical workloads
• Experience supporting quantitative researchers

Preferred Qualifications

• Experience with workflow orchestration, columnar data, and cloud research environments
• A record of improving speed without weakening correctness or auditability
• Experience collaborating across time zones while maintaining the operating coverage assigned to the Albuquerque, NM opening.

Benefits

• Medical, dental, and vision plan options with substantial company support
• 401(k) plan with company matching
• Flexible paid time off and company holidays
• Paid parental and caregiver leave
• Annual learning, conference, and professional-development budget
• Remote-work equipment and home-office support
• Performance-bonus and equity eligibility based on role and level

Benefits are subject to plan terms and eligibility requirements.

How to Apply

Submit a current resume through the application form for the Albuquerque, NM opening. A short cover letter is optional. We will contact qualified applicants about the interview process and next steps.

Equal Opportunity

Anemoi provides equal employment opportunities without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other status protected by applicable law.